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conferences
Challenges in Data-Driven Modelling of Acoutical Systems: A State-Space Perspective Permalink
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Data-driven MOR Methods
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System Identification with pyMOR Permalink
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pyMOR School 2023
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Data-driven Methods: Theory and Practice
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Data-driven and Low-rank Implementations of the Generalized Singular Perturbation Algorithm Permalink
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Data-driven and Low-rank Implementations of the Generalized Singular Perturbation Algorithm
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Data-driven Methods: Theory and Practice
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Making ERA Adaptive
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Acoular Workshop
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Getting Started with Acoular
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portfolio
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publications
Efficient Forced Response Computations of Acoustical Systems with a State-Space Approach
Published in Acoustics, 2021
My master thesis. Reduced order modelling for acoustic systems.
Recommended citation: Pelling, A.J.R. and Sarradj, E. (2021) “Efficient Forced Response Computations of Acoustical Systems with a State-Space Approach,” Acoustics, 3(3), pp. 581–593. Available at: https://doi.org/10.3390/acoustics3030037.
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Noise prediction from the measured surface-vibration of a casing structure by using compressed sensing and finite element method
Published in Applied Acoustics, 2023
A compressed sensing method for noise prediction in an industrial application in cooperation with Rolls-Royce Deutschland.
Recommended citation: Mustafi, P. et al. (2023) “Noise prediction from the measured surface-vibration of a casing structure by using compressed sensing and finite element method,” Applied Acoustics, 211, p. 109527. Available at: https://doi.org/10.1016/j.apacoust.2023.109527.
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A Framework for Generating Large-Scale Microphone Array Data for Machine Learning
Published in Multimedia Tools and Applications, 2023
AcouPipe: A machine learning extension for Acoular.
Recommended citation: Kujawski, A. et al. (2023) “A framework for generating large-scale microphone array data for machine learning,” Multimedia Tools and Applications. Available at: https://doi.org/10.1007/s11042-023-16947-w.
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Snapshot-driven Rational Interpolation of Parametric Systems
Published in arXiv, 2024
Rational interpolation of parametric systems from non-parametric snapshot realizations.
Recommended citation: Pelling, A.J.R. et al. (2024) “Snapshot-driven Rational Interpolation of Parametric Systems.” arXiv. Available at: https://doi.org/10.48550/arXiv.2406.01236.
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MIRACLE — A Microphone Array Impulse Response Dataset for Acoustic Learning
Published in EURASIP Journal on Audio, Speech, and Music Processing, 2024
A comprehensive dataset of anechoic impulse responses.
Recommended citation: Kujawski, A., Pelling, A.J.R. and Sarradj, E. (2024) “MIRACLE—a microphone array impulse response dataset for acoustic learning,” EURASIP Journal on Audio, Speech, and Music Processing, 2024(1), p. 32. Available at: https://doi.org/10.1186/s13636-024-00352-8.
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Towards an Efficient Shifted Cholesky QR for Applications in Model Order Reduction using pyMOR
Published in arXiv, 2025
Modifications of the shifted Cholesky QR Algorithm and efficient implementation im pyMOR.
Recommended citation: Bindhak, M., Pelling, A.J.R. and Saak, J. (2025) “Towards an Efficient Shifted Cholesky QR for Applications in Model Order Reduction using pyMOR.” arXiv. Available at: https://doi.org/10.48550/arXiv.2507.07788.
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SRIRACHA: Shoebox Room Impulse Response Archive with Varying Absorption
Published in TU Berlin depositonce, 2025
A comprehensive dataset of room impulse responses extending the MIRACLE dataset.
Recommended citation: Pelling, A.J.R., Kujawski, A. and Sarradj, E. (2025) “SRIRACHA: Shoebox Room Impulse Response Archive with Varying Absorption.” Available at: https://depositonce.tu-berlin.de/handle/11303/25123 (Accessed: October 30, 2025).
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Adaptive reduced order modelling of acoustic LTI systems with input–output dead time
Published in Mechanical Systems and Signal Processing, 2025
A randomized and adaptive modifcation of Eigensystem Realization Algorithm and a dead time extraction method for acoustical systems.
Recommended citation: Pelling, A.J.R. and Sarradj, E. (2026) “Adaptive reduced order modelling of acoustic LTI systems with input–output dead time,” Mechanical Systems and Signal Processing, 242, p. 113613. Available at: https://doi.org/10.1016/j.ymssp.2025.113613.
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
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